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evedesign: accessible biosequence design with a unified framework

March 9, 2026

Author(s)

David Ross, Thomas Hopf, Artem Gazizov, Sergio Garcia Busto, Ethan Eschbach, SunJae Lee, Milot Mirdita, Ian Ross, Rose Orenbuch, Khaoula Belahsen, Anthony Gitter, Chris Sander, Martin Steinegger, Simon d'Oelsnitz, Debora Marks

Machine learning methods for protein engineering are rarely interoperable, require bespoke workflows, and remain inaccessible to non-experts. Yet the design problems that matter most - conditional design subject to real-world constraints, multi-objective

Mapping the phenotypic landscape of a transcriptional repressor using Deep Mutational Scanning and Growth-based Quantitative Sequencing

December 2, 2025

Author(s)

Zachary Jansen, Xuan Le, Qiyao Wei, Devon Kulhanek, Nina Alperovich, Olga Vasilyeva, Andrew Gilmour, David Ross, Ross Thyer

CymR is a TetR-family transcriptional repressor that recognizes a well-defined operator sequence in the promoter PcymRC. The native ligand cuminic acid and a series of structurally related aromatic acids can bind at an allosteric site and induce a

Experimental Evaluation of AI-Driven Protein Design Risks Using Safe Biological Proxies

June 20, 2025

Author(s)

Svetlana Ikonomova, Bruce Wittmann, Fernanda Piorino Macruz de Oliveira, David Ross, Samuel Schaffter, Olga Vasilyeva, Elizabeth Strychalski, Eric Horvitz, James Diggans, Sheng Lin-Gibson, Geoffrey Taghon

Advances in machine learning are providing new abilities for engineering biology, promising leaps forward with beneficial applications. At the same time, these advances raise concerns about biosecurity. Recently, Wittmann et al. described an in silico

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